HuffPost is not normally the go-to for business information but this is great online piece that asks 12 members of Young Entrepreneur Council (YEC) their opinion on the top mistake companies make with big data. I’ll list a few below and the link to the article is at the bottom.
CPG companies working with retailer supplied data should make of note of this.
Not Making Data-Driven Decisions
Data equals power.
“I believe that most companies don’t realize how much you can pull out of your data. There are many tools out there that can help you make data-driven decisions, which in turn can give you more predictable results.” – Elliot Bohm, Cardcash.com
Not Having Data Scientists
“Collecting big data is easier then ever and implementing tools to work with big data has also become much more accessible. The problem is oftentimes companies do not have a qualified Data Scientist or someone who can interpret or map/reduce the proper dimensions of data. Instead they rely on non-qualified personnel to interpret data. The improper analysis of data can be very harmful to a company.” – Phil Chen, Systems Watch
Answering Trivial Questions With It
“The biggest mistake that companies make with big data is using it to answer relatively trivial questions such as “what.” Big data isn’t about “what” questions; it’s about “why” questions. Big data is about joining data sets that have never been joined before and asking questions that have never been asked. It’s about knowing why customers and employees are doing the things that they do.” – Dusty Wunderlich, Bristlecone Holdings
Focusing on Data Processing at the Expense of Analysis
“Half of the challenge of big data is finding the right algorithms and approaches to ingest the vast quantities of information you have. The second, and more overlooked, challenge is finding a way to present your findings in a usable fashion. Too many companies focus on the former (how do we process all that data?) at the expense of the latter (how do we make it actionable?).” – AJ Shankar, Everlaw, Inc.
Confusing Correlation and Causation
“When companies work with big data, a major and common mistake is to assume that correlation implies causation. While you can use data to understand correlation, equating it to “cause and effect” can lead to false results and fruitless decisions. Making the distinction between correlation and root cause is critical to utilizing data for best results.” – Doreen Bloch, Poshly Inc.
Not Using It to Answer Business Questions
“There’s so much data being generated and collected, it can be overwhelming. Successful organizations start with the business questions they want to answer and then assess the data they have to answer those questions. Just looking at your mountain of data and trying to figure out what to do with it is a recipe for a lot of wasted time and effort.” – David Booth, Cardinal Path
There are additional ideas at the online article.